Ecommerce analytics are tricky to begin with. Add tracking your subscription services on top of that and you’re dealing with a whole other animal! Do you use Google Analytics to report on your Shopify store’s one-off purchases AND recurring orders? Check out our video on Littledata’s advanced checkout funnel analysis to find out how we’ve made subscription analytics easy. https://youtu.be/EU3Cj2Z6AII Traditional ecommerce stores typically track one checkout funnel per property. The benefit is that this makes it easy to analyze the drop-off at each point. But, if you have multiple checkouts to track one-time orders and subscription purchases, important insights might go unnoticed when GA aggregates your data. Littledata automatically differentiates between your checkout funnels to show whether they’re subscription or one-time purchases. That way you know exactly what each funnel’s checkout completion rate is for different order types. This gives you the power to tailor your remarketing strategies for specific checkouts or products, further increasing your ads’ relevance to possible customers. Note: Do you trust your subscription tracking? Get accurate subscription tracking with the ultimate ReCharge guide for Shopify Littledata integrates with the top subscription ecommerce apps—including ReCharge Payments, Bold Commerce, and Ordergroove—and automatically tracks both Shopify and subscription checkouts. “Littledata is a must-have if you’re running Recharge and Shopify; it helped us figure out what channels were getting us our future subscribers and what helped convert them.” —Better Way Health To access your checkout reports in Google Analytics, go to your ecommerce analysis reports. From there, you can view your checkout behavior reports to get a general understanding of when users are dropping off throughout the checkout process. Find out how to segment your data between Shopify and subscription checkouts to measure the exact drop-off rate at each stage of the checkout process for each checkout funnel in our latest learning video. Capture data at every turn In addition to tracking your checkout funnel completion rates for subscription checkouts, Littledata tracks crucial sales and marketing metrics, so you can:  Get accurate marketing attribution data for subscription revenue, including first-time payments and recurring chargesUse custom dimensions to measure customer lifetime value (LTV)Track performance by payment source, subscription plan type, and product categoryView complete sales and marketing data with combined server-side and client-side trackingMake better, informed decisions for your Shopify store Resources Watch a quick demo video on how Littledata worksFind out how to calculate LTV with Google AnalyticsDownload the ultimate guide to subscription trackingCheck out our ReCharge FAQSubscribe to our YouTube Channel for more videos about analytics

Many of our customers come to us with a similar question: "how do I measure ecommerce lifetime value (LTV)?" The latest episode in our Learning Videos series shows you how to do just that for both your one-off purchasers and subscription customers. Our step-by-step tutorial covers two methods of calculating customer LTV using your Google Analytics (GA) data. You'll get to know Littledata’s custom dimensions in GA and learn how to visualize your calculations in Google Data Studio. During installation, Littledata automatically creates several custom dimensions in your connected Google Analytics property. These custom dimensions include: Lifetime Revenue, the sum total a customer has spent in your Shopify store (including one-time purchases and subscription orders) Shopify Customer ID, the unique identifier Shopify assigns to each customer Last Transaction Date Payment Gateway Purchase Count They offer better data to help you understand your customers' buying behavior, then calculate and visualize their LTV. To kick things off, you'll first need to export your data from GA to Google Sheets or another spreadsheet tool via CSV. Once you’ve enabled the GA add-on in Google Sheets, you're ready to get started. Method 1: Calculate LTV by Lifetime Revenue, Shopify Customer ID, and Transaction Count In the first method of calculating lifetime value, we’ll use Transactions as the metric. The dimensions we'll use—Shopify Customer ID and Lifetime Revenue—correspond with ga:dimension5 and ga:dimension3, respectively. Use the image below as a guide to set up your report: Next, set your Metrics Reference as Transactions and your Dimensions Reference as Custom Dimensions. After you run the report, Google Sheets should look something like this: Finally, use Google Sheets' built-in functions to calculate the average or median LTV of your customers. Method 2: Calculate LTV by Source/Medium, Transaction ID, Shopify Customer ID, and Transaction Revenue This second LTV calculation method helps you track which marketing channels bring in your most valuable customers: the ones who spend the most over time. In this method, use Transaction Revenue as the metric and Source/Medium, Transaction ID, and Shopify Customer ID as the metrics. These correspond with ga:sourceMedium, ga:transactionId, and ga:dimension1 respectively. This method requires the widest date range possible to capture the most transactional data possible—preferably since you started using Littledata. Before running the report, your Google Sheet should appear as follows: After exporting your data, your result will look like this—a list of transactions with source/medium and revenue data: Next, select all the data in your report to create a pivot table, aggregating by source/medium per customer. The result will reveal the total revenue per customer, per source. After completing the pivot table, you're ready to visualize your data in Data Studio. Build Reports in Google Data Studio Google Data Studio is one of our recommended reporting tools for ecommerce sites. Why? Because it's free, powerful, and works really well with Google Analytics. The first step in visualizing your data is to import your data into Google Data Studio by setting Google Sheets as your source. To do this, select your Google Sheets file followed by the pivot table you created in the previous method, and add it to your report in Google Data Studio. Change the data source by setting the aggregation to median so results yield the median lifetime revenue per traffic source. Your report dimension should be set to ga:sourceMedium and your metrics should be set to ga:transactionrevenue and ga:dimension1. Modify Shopify Customer ID from sum to count distinct to reveal the total unique customer IDs, which we'll use to sort our data. Sort by Shopify Customer ID to see the traffic source that brings the most customers to your site. The resulting report shows you the median lifetime revenue per traffic source, sorted by the total customers per source. References Quick Tips for Subscription Stores Using Custom Dimensions in GA 3 Deep Dives into Customer Lifetime Value for Ecommerce Sites LTV from GA vs LTV provided by Littledata How to Calculate Customer Lifetime Value in GA for Shopify Stores Custom Dimensions for Calculating Customer Lifetime Value Subscription Analytics Does Littledata work with my ecommerce reporting tool?

One of the challenges subscription businesses face is differentiating between order types.  The problem For Shopify merchants, offering single purchase options complicates things even more — with single purchase options, order data will show in two places (Shopify and ReCharge). This leads to a major disconnect between user behaviour and orders, unable to leverage the full potential of Google Analytics.  At this point, you probably have a multitude of “known unknowns”, such as: Which traffic sources drive more first time subscription orders? What's my conversion rate on one time purchases? What's my average customer lifetime value? Do my one time purchasers end up converting to subscribers? What's my churn rate month over month? [tip]Get accurate tracking for repeat orders with the ultimate Shopify ReCharge guide.[/tip] The solution Bridging the gap with Littledata Littledata helps bridge different platforms by linking orders betweenShopify, ReCharge and Google Analytics.  [subscribe] Differentiating between order types With Littledata’s improved tracker, merchants can differentiate between order types. For this, we use the Affiliation dimension.  In the Google Analytics report, it will look something like this:  Right away, this information answers a few questions: What is the distribution between my order types? Are my recurring subscription orders growing month over month? Is the average order value (AOV) of subscribers higher than that of one time purchasers?  Both of these can be viewed in this custom report. What traffic sources drive the most sales?  One of the questions our team is asked most often is what sources of traffic drive the most subscription orders?  Short answer: the Affiliation dimension can be used as a secondary dimension in the source/medium reports, or use this custom report.  By using filters to single out an order type, you can easily determine what traffic sources drive the most first time subscription orders. Segment more Segmentation opens up new ways to look at the data as well. Creating two segments for one time purchases and first subscription purchases, you can see how the two types of purchases differ.  Look for behavioural differences like:  Do One Time purchasers AOV higher or lower compared to First Subscription orders? Are users testing the product first and then committing to a subscription?  Littledata custom dimensions Google Analytics custom dimensions are an excellent way to expand your data collection and reporting power. With our Shopify app, Littledata adds these custom dimensions: Littledata - Shopify Customer ID Littledata - Last Transaction Date Littledata - Purchase Count Littledata - Lifetime Revenue Littledata - Payment Gateway With the help of these custom dimensions, we can answer the following questions:  What's my median customer lifetime value (CLV)? How many purchases do customers make in their lifetime? What's my churn rate month over month? Since these are custom dimensions, they cannot be aggregated on Google Analytics, meaning the data will need to be displayed using a different method. For this, we’ll use Google Sheets with the Google Analytics add-on to query the data and pivot tables.  Step 1 - Query all the data you need Metrics Avg. Order Value Revenue Dimensions Littledata - Shopify Customer ID  Littledata - Lifetime Revenue Littledata - Purchase Count Affiliation - to differentiate between the order types.  It should look something like this:  In this case, the custom dimensions are at index 4, 6 and 8. This may differ depending on your setup.  Step 2 - Run the report After you run the report, this will create another sheet in your document. It will look something like this:  Step 3 - Create a pivot table  In the rows section, add the Affiliation dimension to differentiate between the order types.  Shopify will mean a one time purchase (normal purchase). The other two order types are the first subscription order and recurring order.  In the values area, add:  The user IDs summarised by countunique The customer lifetime value summarised by median so that we have the median LTV. We use median over average so that this number is not influenced too much by the outliers.  Purchase count summarised by median.  Average order value  The end result should look something like this:  Step 4 - Interpret the data In this report, we can instantly draw some conclusions:  Most customers make single purchases rather than subscribing  Subscription first order median purchase is 2, so this means users have purchased in the past before committing to a subscription Subscribers purchase 8 times (median value), with a median CLV is around $500.  How to take this further Since we know most customers order at least once before committing to a subscription, we can calculate the average number of days between a single purchase and a first subscription purchase.  When you’re armed with that type of information, you can adjust your email marketing flows accordingly and adjust your remarketing campaigns to shorten or lengthen the number of days your ads show to leads.  With the help of the Customer IDs, we can also calculate the month over month churn rate (we’ll get to that in a follow-up post). It's your turn now How do you use these additional events and custom dimensions in your segmentation?  What was your biggest insight using these events and custom dimensions?  How did it influence your marketing campaigns? Share your experience (and current approach with GA) via the live chat in the bottom corner. I'm curious about the different ways you make use of these additional data points! In the meantime, our team is at the ChargeXSummit in Santa Monica sharing all about our ReCharge connection for subscription-based stores. [note]Now, with a revamped ReCharge connection — ReCharge v2 — you can track subscription lifecycle events with ease![/note]